Inhibitors and Enablers as Dual Factor Concepts in Technology Usage

Information systems (IS) research has focused extensively on the factors that foster adoption and usage. A large body of work explores overall beliefs about system usage, antecedents of system satisfaction, and other perceptions that enable system success, create positive attitudes, and encourage usage. However, much less attention has been given to what perceptions uniquely inhibit usage. In large part, this is due to the implicit assumption that the inhibitors of usage are merely the opposite of the enablers. This paper proposes a theory for the existence, nature, and effects of system attribute perceptions that lead solely to discourage use. I posit that usage inhibitors deserve an independent investigation on the basis of three key arguments. One, there exist perceptions that serve solely to discourage usage, and these are qualitatively different from the opposite of the perceptions that encourage usage. Two, these inhibiting and enabling perceptions are independent of one another and can coexist. Three, inhibiting and enabling perceptions have differing antecedent and consequent effects.. As unique beliefs, inhibiting perceptions can add to our understanding of the antecedents of usage or outright rejection. Further, such inhibitors may not only be important to the IS usage decision, they may be more important than enabling beliefs

Patients’ Resistance towards Health Information Technology A Perspective of the Dual Factor Model of IT Usage

This paper presents a research model of patients’ resistance towards Health Information Technology (HIT). In particularly it examines patients’ reactions towards a new Patient Portal System (PPS). This work provides an integration of the technology acceptance and resistance to change literatures. The Resistance to Change construct from the User Resistance Model (URM), and the Unified Theory of Acceptance and Use of Technology (UTAUT) are bridged using the dual-factor model of technology usage. This model explains the asymmetric effects of use inhibitors such as Resistance to Change on use enablers such as Performance Expectancy and Effort Expectancy. The integrative model is empirically supported using survey data collected from patients of a large public international hospital. Total of 265 valid responses were used for the data analysis. This study highlights the importance of integrating resistance to change with the technology use research especially in healthcare settings that is considered to be under researched. Moreover, it is considered to be one of the first studies in IS that brings in patients’ perspectives of new HIT

PATIENTS’ ACCEPTANCE AND RESISTANCE TOWARD THE HEALTH CLOUD: AN INTEGRATION OF TECHNOLOGY ACCEPTANCE AND STATUS QUO BIAS PERSPECTIVES

The latest technological trends such as health cloud provide a strong infrastructure and offer a true enabler for healthcare services over the Internet. Despite its great potential, there are gaps in our understanding of how users evaluate change related to the health cloud and decide to resist it. According to the technology acceptance and status quo bias perspectives, this study develops an integrated model to explain patients’ intention to use and resistance to health cloud services. A field survey was conducted in Taiwan to collect data from patients. The structural equation model was used to examine the data. The results showed that patient resistance to use was caused by inertia, perceived value, and transition costs. Perceived usefulness (PU) and perceived ease of use (PEOU) have positive and direct effects on behavioral intention to use, and PEOU appears to have a positive direct effect on PU. The results also indicated that the relationship between intention to use and resistance to use had a significant negative effect. Our study illustrates the importance of incorporating user resistance in technology acceptance studies in general and health technology usage studies in particular, grounds for a resistance model of resistance that can serve as the starting point for future research in this relatively unexplored yet potentially fertile area of research

Explaining Physicians’ Acceptance and Resistance to the NHI Pharmacloud: A Theoretical Model and Empirical Test

The PharmaCloud allows physicians to streamline many of their healthcare processes and ensure patient safety in a more efficient and cost-effective manner. Despite its great potential, however, there are gaps in our understanding of how physicians evaluate change in relation to the PharmaCloud and why they decide to resist it. Thus, this study develops an integrated model to explain physicians’ intention to use the PharmaCloud and their intention to resist it. A field survey was conducted in Taiwan to collect data from physicians. Structural equation modeling (SEM) using the partial least squares (PLS) method was employed to test the research model. The results show that physicians’ resistance to the use of the PharmaCloud is the result of regret avoidance, inertia, perceived value, transition costs, and perceived threat. Information quality, system quality, and service quality are shown to have positive and direct effects on physicians’ intention to use the PharmaCloud. Our study illustrates the importance of incorporating user resistance in technology acceptance studies in general and health technology usage studies in particular, providing grounds for a model of resistance that can serve as the starting point for future research in this relatively unexplored yet potentially fertile area of research

Use of Clouds-Based Regional Management Systems : Dual Factor Theory Approach

The purpose of this research is to investigate the enablers and inhibitors include dual factor theory of clouds based regional information system usage. This research took samples of financial employees who worked in the Regional Apparatus Organizations (OPD) in Jember Regency consisting of 200 respondents, used a survey method and primary data. The sample selection technique in this study uses purposive sampling, data analysis uses multiple regression. The results show, the first problem of IT infrastructure has a negative effect on the use of cloud-based regional management information systems. Secondly, the problem of human resource competency has a negative effect on the use of cloud-based regional management information systems. Third, perceived usefulness has a positive effect on the use of cloud-based regional management information systems. Fourth, perceived ease of use has a positive effect on the use of cloud-based regional management information systems

Enabelers and Inhibitors of Healthcare Information Technology Adoption: Toward a Dual-Factor Model

This paper formulates, operationalizes, and empirically validates a dual-factor model of healthcare information technology (HIT) adoption, by taking into account both the enabling factors driving HIT adoption and the inhibiting factors constraining such adoption. Perceived usefulness and perceived ease of use were examined as enablers and perceived loss of control as an inhibitor. Using survey data on adoption of a new computerized patient order entry system among physicians at a community hospital, we demonstrate that inhibitors not only have a negative effect on one’s intention to adopt HIT systems, counteracting the positive effect of enablers, but also negatively bias some of the enabling perceptions. The overall negative impact posed by inhibitors may override and surpass any positive impact posed by a multitude of enablers. Implications of our findings for HIT research and practice are discussed

Positive and negative word of mouth (WOM) are not necessarily opposites: A reappraisal using the dual factor theory

Prior research has not systematically investigated the enablers and inhibitors in conjunction to measure consumer behavior toward mobile wallets (m-wallets), focusing either on the adoption or the resistance perspective only. Similarly, antecedents and consequences of the dichotomous nature of word of mouth for m-wallets have also remained obscure so far. The present research proposes to address this void in the accumulated learnings by examining both enablers and inhibitors of mobile wallets (m-wallets) as antecedents of valence of word of mouth (positive and negative; PWOM and NWOM, respectively). Grounded in Dual Factor Theory, this study aims to explore consumers’ continued use intentions resulting from the WOM valence. The findings reveal that enablers (perceived information quality, perceived ability, and perceived benefit) drive PWOM, while the inhibitors (perceived cost, perceived risk, and perceived uncertainty) spur NWOM. Furthermore, the results show that only PWOM drives the continuance intentions of m-wallet users. Therefore, the study proves that the antecedents of PWOM are different from those of NWOM.publishedVersio

Perceived creepiness in response to smart home assistants: A multi-method study

Smart home assistants (SHAs) have gained a foothold in many households. Although SHAs have many beneficial capabilities, they also have characteristics that are colloquially described as creepy – a fact that may deter potential users from adopting and utilizing them. Previous research has examined SHAs neither from the perspective of resistance nor the perspective of creepiness. The present research addresses this gap and adopts a multi-method research design with four sequential studies. Study 1 serves as a pre-study and provides initial exploratory insights into the concept of creepiness in the context of SHAs. Study 2 focuses on developing a measurement instrument to assess perceived creepiness. Study 3 uses an online experiment to test the nomological validity of the construct of creepiness in a larger conceptual model. Study 4 further elucidates the underlying behavioral dynamics using focus group analysis. The findings contribute to the literature on the dark side of smart technology by analyzing the triggers and mechanisms underlying perceived creepiness as a novel inhibitor to SHAs. In addition, this study provides actionable design recommendations that allow practitioners to mitigate end users’ potential perceptions of creepiness associated with SHAs and similar smart technologies

Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model

This study investigates the factors that build resistance and attitude towards AI voice assistants (AIVA). A theoretical model is proposed using the dual-factor framework by integrating status quo bias factors (sunk cost, regret avoidance, inertia, perceived value, switching costs, and perceived threat) and Technology Acceptance Model (TAM; perceived ease of use and perceived usefulness) variables. The study model investigates the relationship between the status quo factors and resistance towards adoption of AIVA, and the relationship between TAM factors and attitudes towards AIVA. A sample of four hundred and twenty was analysed using structural equation modeling to investigate the proposed hypotheses. The results indicate an insignificant relationship between inertia and resistance to AIVA. Perceived value was found to have a negative but significant relationship with resistance to AIVA. Further, the study also found that inertia significantly differs across gender (male/female) and age groupings. The study's framework and results are posited as adding value to the extant literature and practice, directly related to status quo bias theory, dual-factor model and TAM

INTRUSIVE SMART HOME ASSISTANTS: AN EXPLORATORY STUDY AND SCALE DEVELOPMENT

Despite having many useful capabilities, more recently smart home assistants (SHAs) have also raised negative feelings and doubts which may cause resistance among potential users. However, current research has neither examined SHAs from the perspective of resistance nor its specific drivers (inhibitors). We address this gap and adopt a mixed-method research design with two studies that build on each other. Study 1 (N=10) elicits the belief structures underlying resistance to SHAs. Study 2 (N=276) builds on these findings and delves deeper into the understanding of one novel identified inhibitor, namely “perceived intrusion”, by taking initial strides towards creating a measurement instrument. Our results contribute to the previously under-researched “dark side” of smart consumer IT by examining the phenomenon of resistance. This way, we hope to inspire future research to expand on our findings, as well as apply our measurement instrument in other smart product contexts